Joint Beamforming Design for Multiuser MISO Downlink Aided by a Reconfigurable Intelligent Surface and a Relay
Type
ArticleAuthors
Obeed, Mohanad
Chaaban, Anas

KAUST Grant Number
OSR2018-CRG7-3734Date
2022-04-12Permanent link to this record
http://hdl.handle.net/10754/685137
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Reconfigurable intelligent surfaces (RISs) have drawn considerable attention due to their ability to direct electromagnetic waves into desirable directions. Although RISs share some similarities with relays, the two have fundamental differences impacting their performance. To harness the benefits of both, we propose a downlink system wherein a relay and an RIS improve performance in terms of energy-efficiency. Using singular value decomposition (SVD), semidefinite programming (SDP), and function approximations, we propose different solutions for optimizing the beamforming matrices at the base-station (BS), the relay, and the phase shifts at the RIS to minimize the total power under quality-of-service (QoS) constraints. The problem is solved when the relay operates in half-duplex and full-duplex modes and when the reflecting elements have continuous and discrete phase shifts. Simulation results compare the performance of the system with and without the RIS or the relay, under different optimization solutions. The results show that the system with full-duplex relay and RIS outperforms the other scenarios, and the contribution of full-duplex relay is higher than that of the RIS. However, an RIS outperforms a half-duplex relay when the required QoS is high. The results also show that increasing the number of reflecting elements improves the performance better in the presence of a relay than in its absence.Citation
Obeed, M., & Chaaban, A. (2022). Joint Beamforming Design for Multiuser MISO Downlink Aided by a Reconfigurable Intelligent Surface and a Relay. IEEE Transactions on Wireless Communications, 21(10), 8216–8229. https://doi.org/10.1109/twc.2022.3164903Sponsors
This work was supported by the King Abdullah University of Science and Technology (KAUST) under Award OSR2018-CRG7-3734.Additional Links
https://ieeexplore.ieee.org/document/9756313/ae974a485f413a2113503eed53cd6c53
10.1109/TWC.2022.3164903